Species mapping is an essential tool for conservation programmes as it provides clear pictures of the distribution of marine resources. However, in fishery ecology, the amount of objective scientific information is limited and data may not always be directly comparable. Information about the distribution of marine species can be derived from two main sources: fishery-independent data (scientific surveys at sea) and fishery-dependent data (collection and sampling by observers in commercial vessels). The aim of this paper is to compare whether these two different sources produce similar, complementary, or different results. We compare them in the specific context of identifying the Essential Fish Habitats of three elasmobranch species (S. canicula, G. melastomus, and E. spinax). Similarity and prediction statistics are used to compare the two different spatial patterns obtained by applying the same Bayesian spatio-temporal modelling approach in the two sources. Results showed that the spatial patterns obtained are similar, although differences are present. In particular, models based on fishery-dependent data are better able to identify temporal relationships between the probability of presence of the species and seasonal environmental variables. In contrast, fishery-independent data better discriminate spatial locations where a species is present or absent. Besides the spatial and temporal differences of the two datasets, the consistency of habitat results highlights the inclusion in each dataset of most of the environmental envelope of each species, both in time and space. Consequently, sampling data should be adapted to each species to reasonably cover their environmental envelope, and a combination of datasets will likely provide a better habitat estimation than using each dataset independently. These findings can be useful in helping fishery managers improve definition of survey design and analyses.

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a b s t r a c tIdentifying the factors that affect the spatial distribution of marine biodiversity is a central issue to ecology. This knowledge is crucial to evaluate biodiversity patterns, to predict the impact of environmental change and anthropogenic activities, and to design accurate management programs. Here, we investigated the degree to which environmental features, human activities and spatial constraints interact and influence spatial gradients in marine biodiversity using the Western Mediterranean Sea as a model system. Our results revealed that a large fraction of the variability in biodiversity metrics of most marine groups analysed is accounted for by the joint effect of environment and human activities, environment and spatial variables or between all three groups of variables. In other words, major environmental variables and human activities have a collinear spatial structure, and thus an important part of the variation in biodiversity metrics can be attributed to these three groups of explanatory variables. Among pure effects, deviance partitioning results showed that the effect of environmental variables was more evident than the effect of human or spatial variables. The effect of single environmental and human variables considered in the analyses was different for different marine groups. This study contributes to the knowledge of the effects of ecological factors on the spatial distribution of marine biodiversity in the Mediterranean Sea, which is important in the development of more complex spatial analyses. Our results support the hypothesis that the joint effect of different predictor sets can be highly relevant in spatial patterns of biodiversity due to spatial collinearity. Thus, the simultaneous analysis of the relative effect of ecologically important predictor sets is important in preventing misinterpretations of the ecological mechanisms that explain spatial distribution of marine biodiversity.

With the aim of improving artificial fertilization (AF) in turbot, Scophthalmus maximus (L.), a series of fertilization experiments was carried out under dry conditions and different wet conditions (eggs/sea water: 2V/V and V/V). Another series of fertilization experiments was carried out with different quantities of sperm pool to determine the optimal ratio of spermatozoa to eggs for each AF method. Sperm pool from two males and eggs from spawns with a viability rate of > 70% were used. The sperm pool’s density (0.4–5.18 × 109 sperm mL–1) and motility (1–5) had been assessed previously. Significantly different fertilization rates were found when comparing 2V/V and V/V wet conditions. Significantly higher fertilization rates were found in dry fertilization when the sperm–egg ratio was > 9000 spermatozoa per egg and, under wet condition V/V, at 3000–4000 spermatozoa per egg.

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